Aim

• Examine associations between SES variables and Anatomical Features of Language Regions in young children with and without ASD
• Conduct sensitivity analyses to examine whether findings are robust to the inclusion of data rated Q>=3 (vs. Q>=4)

Analytical Approach: Anatomical Measures

• Local Gyrification Index (LGI)
• Cortical Thickness
• Surface Area

Analytical Approach: SES Measures

• Income:Needs Ratio (household income divided by federal poverty level, adjusted for household size)
• Maternal Educational Level
• Median Income by Postal Code
• Neighborhood Advantage Index
  • PCA on neighborhood variables at the census tract level

Neighborhood Advantage PCA Results

• PCA on neighborhood variables at the census tract level
  • Average Household Income
  • % Living in Poverty
  • Median Household Rent
  • Median home value
  • % of Households with public assistance
  • % of Individuals with a bachelor’s degree
  • 

Participants Q>=4

Participants Q>=3

## 
## 
## |                      | level  |          ASD          |           TD           |   p    | test |
## |:-------------------------:|:------:|:---------------------:|:----------------------:|:------:|:----:|
## |           **n**           |        |          28           |           27           |        |      |
## |        **SEX (%)**        | Female |       6 (21.4)        |       14 (51.9)        | 0.039  |      |
## |                           |  Male  |       22 (78.6)       |       13 (48.1)        |        |      |
## |  **V1.Age (mean (SD))**   |        |     39.39 (13.77)     |     39.56 (13.98)      | 0.965  |      |
## |  **MEL_cat (mean (SD))**  |        |      3.52 (1.60)      |      4.33 (1.05)       | 0.049  |      |
## |    **INR (mean (SD))**    |        |      3.35 (2.79)      |      4.37 (2.10)       | 0.180  |      |
## | **zipIncome (mean (SD))** |        |  53477.39 (18001.70)  |  57480.76 (15744.99)   | 0.439  |      |
## |   **SES1 (mean (SD))**    |        |     -0.40 (2.06)      |      0.62 (1.76)       | 0.054  |      |
## | **ExpLang_T (mean (SD))** |        |     31.67 (11.07)     |     49.78 (11.10)      | <0.001 |      |
## | **RecLang_T (mean (SD))** |        |     32.32 (11.85)     |     53.85 (10.96)      | <0.001 |      |
## |  **ELC_SS (mean (SD))**   |        |     71.96 (20.00)     |     105.67 (15.78)     | <0.001 |      |
## |    **TBV (mean (SD))**    |        | 1077031.79 (96937.48) | 1050164.41 (111924.89) | 0.345  |      |
## 
## Table: Participant Summary Table for Q>=4

## 
## 
## |                      | level  |          ASD           |           TD           |   p    | test |
## |:-------------------------:|:------:|:----------------------:|:----------------------:|:------:|:----:|
## |           **n**           |        |           36           |           31           |        |      |
## |        **SEX (%)**        | Female |       10 (27.8)        |       14 (45.2)        | 0.221  |      |
## |                           |  Male  |       26 (72.2)        |       17 (54.8)        |        |      |
## |  **V1.Age (mean (SD))**   |        |     39.03 (12.95)      |     37.61 (14.20)      | 0.671  |      |
## |  **MEL_cat (mean (SD))**  |        |      3.54 (1.50)       |      4.36 (0.99)       | 0.019  |      |
## |    **INR (mean (SD))**    |        |      3.46 (2.75)       |      4.13 (2.14)       | 0.319  |      |
## | **zipIncome (mean (SD))** |        |  54158.10 (18734.17)   |  56118.68 (15004.41)   | 0.675  |      |
## |   **SES1 (mean (SD))**    |        |      -0.35 (1.97)      |      0.54 (1.66)       | 0.053  |      |
## | **ExpLang_T (mean (SD))** |        |     32.62 (11.76)      |     48.77 (11.52)      | <0.001 |      |
## | **RecLang_T (mean (SD))** |        |     32.49 (12.52)      |     53.32 (11.13)      | <0.001 |      |
## |  **ELC_SS (mean (SD))**   |        |     72.23 (19.97)      |     104.94 (16.57)     | <0.001 |      |
## |    **TBV (mean (SD))**    |        | 1076827.78 (100384.08) | 1045805.34 (115665.34) | 0.244  |      |
## 
## Table: Participant Summary Table for Q>=3

Distributions of Variables: Neighborhood Advantage, Q>=4

Q>=4 Kolmogorov Smirnov Test: D=0.27, p = 0.25 (distributions not significantly different from one another).

Neighborhood Advantage Histograms, Q>=3

Q>=3 Kolmogorov Smirnov Test: D=0.21, p = 0.46 (distributions not significantly different from one another).

Histograms: INR Q>=4

Q>=4 Kolmogorov Smirnov Test: D=0.42, p = 0.04 (distributions are significantly different from one another).

INR Histograms, Q>=3

Q>=3 Kolmogorov Smirnov Test: D=0.36, p = 0.06 (distributions not significantly different from one another).

Histograms, MEL Q>=4

Q>=4 Kolmogorov Smirnov Test: D=0.36, p = 0.11 (distributions not significantly different from one another).

MEL Histograms, Q>=3

Q>=3 Kolmogorov Smirnov Test: D=0.32, p = 0.11 (distributions not significantly different from one another).

Histograms: Zip-Income Q>=4

Q>=4 Kolmogorov Smirnov Test: D=0.22, p = 0.67 (distributions not significantly different from one another).

MEL Histograms, Q>=3

Q>=3 Kolmogorov Smirnov Test: D=0.2, p = 0.64 (distributions not significantly different from one another).

Histograms: Age Q>=4

Q>=4 Kolmogorov Smirnov Test: D=0.09, p = 0.99 (distributions not significantly different from one another).

Age Histograms, Q>=3

Q>=3 Kolmogorov Smirnov Test: D=0.12, p = 0.96 (distributions not significantly different from one another).

Anatomical Regions

• From Desikan-Killiany Atlas
  • Transverse temporal gyrus
  • Superior temporal gyrus
  • Middle temporal gyrus
  • Inferior Frontal Gyrus
    • Pars Opercularis
    • Pars Orbitalis
    • Pars Triangularis
  • 

LGI Results: INR, Q>=4

	rh_parsopercularis_lgi
Coeffcient	Estimates	CI (95%)	p-Value
Intercept	3.48	2.46 – 4.50	<0.001
Income:Needs	0.04	0.01 – 0.08	0.026
TBV	0.00	-0.00 – 0.00	0.125
Age	0.01	0.00 – 0.02	0.027
Observations	42
R2 / R2 adjusted	0.342 / 0.290

Income to needs ratio predicts rh_parsopercularis_lgi, controlling for age and TBV in the Q>=4 dataset.

LGI Results: INR, Q>=3

	rh_parsopercularis_lgi
Coeffcient	Estimates	CI (95%)	p-Value
Intercept	3.74	2.91 – 4.58	<0.001
Income:Needs	0.03	0.00 – 0.07	0.045
TBV	0.00	-0.00 – 0.00	0.144
Age	0.01	0.00 – 0.01	0.031
Observations	52
R2 / R2 adjusted	0.289 / 0.244

Income to needs ratio predicts rh_parsopercularis_lgi, controlling for age and TBV in the Q>=3 dataset.

LGI Results, Zip-Income Q>=4

	lh_parsorbitalis_lgi
Coeffcient	Estimates	CI (95%)	p-Value
Intercept	2.68	2.36 – 3.01	<0.001
Zip-Income	0.00	0.00 – 0.00	0.018
Age	0.01	0.00 – 0.01	0.019
Observations	44
R2 / R2 adjusted	0.235 / 0.198

Zip-Income is a significant predictor of lh pars orbitalis LGI when controlling for age (removed TBV because it was not a significant predictor in the model with age and Zip-Income).

Dx not a significant predictor in this model, nor is the diagnosisXzipIncome interaction term.

LGI Results, Zip-Income Q>=3

	lh_parsorbitalis_lgi
Coeffcient	Estimates	CI (95%)	p-Value
Intercept	2.66	2.38 – 2.94	<0.001
Zip-Income	0.00	0.00 – 0.00	0.002
Age	0.01	0.00 – 0.01	0.014
Observations	55
R2 / R2 adjusted	0.267 / 0.239

Zip-Income is a significant predictor or lh pars orbitalis LGI when controlling for age (removed TBV because it was not a significant predictor in the model with age and Zip-Income).

Dx not a significant predictor in this model, nor is the diagnosisXzipIncome interaction term.

CT Results: INR Q>=4

	rh_superiortemporal_CT
Coeffcient	Estimates	CI (95%)	p-Value
Intercept	3.38	3.17 – 3.58	<0.001
Income:Needs	0.02	0.00 – 0.04	0.044
Age	-0.01	-0.01 – -0.00	0.001
Sex	0.03	-0.06 – 0.12	0.449
Observations	46
R2 / R2 adjusted	0.275 / 0.223

INR Predicts LH middle temporal cortical thickness (CT), controlling for age and sex/gender in the Q>=4 dataset.

CT Results: INR, Q>=3 Plots

	lh_middletemporal_CT
Coeffcient	Estimates	CI (95%)	p-Value
Intercept	3.32	3.13 – 3.51	<0.001
Income:Needs	0.02	0.00 – 0.04	0.020
Age	-0.00	-0.01 – -0.00	0.004
Sex	0.03	-0.06 – 0.11	0.507
Observations	56
R2 / R2 adjusted	0.212 / 0.166

	lh_superiortemporal_CT
Coeffcient	Estimates	CI (95%)	p-Value
Intercept	3.09	2.90 – 3.28	<0.001
Income:Needs	0.02	0.00 – 0.04	0.031
Age	-0.00	-0.01 – 0.00	0.096
Sex	-0.01	-0.09 – 0.07	0.801
Observations	56
R2 / R2 adjusted	0.118 / 0.067

	rh_parstriangularis_CT
Coeffcient	Estimates	CI (95%)	p-Value
Intercept	2.77	2.57 – 2.97	<0.001
Income:Needs	0.02	0.00 – 0.04	0.025
Age	-0.00	-0.01 – -0.00	0.027
Sex	0.09	0.00 – 0.18	0.049
Observations	56
R2 / R2 adjusted	0.214 / 0.168

INR Predicts middle temporal gyrus CT as well as lh STG CT and rh pars triangularis CT in the Q>=3 dataset (only predicts middle temporal CT in the Q>=4 dataset).

CT Results: Neighborhood Advantage (SES1), Q>=4

	lh_parsopercularis_CT
Coeffcient	Estimates	CI (95%)	p-Value
Intercept	3.11	2.97 – 3.26	<0.001
SES1	0.02	0.00 – 0.04	0.022
Age	-0.00	-0.01 – -0.00	<0.001
Sex	0.03	-0.04 – 0.10	0.435
Observations	58
R2 / R2 adjusted	0.257 / 0.215

	rh_middletemporal_CT
Coeffcient	Estimates	CI (95%)	p-Value
Intercept	3.26	3.09 – 3.42	<0.001
SES1	0.02	0.00 – 0.04	0.035
Age	-0.00	-0.01 – -0.00	0.008
Sex	0.08	-0.00 – 0.16	0.062
Observations	58
R2 / R2 adjusted	0.196 / 0.151

SES1 predicts lh pars opercularis CT (controlling for age and sex).

SES1 predicts rh middle temporal CT (controlling for age and sex).

TBV not a significant predictor of CT in tested regions, therefore removed as a covariate.

CT Results, Neighborhood Advantage: Q>=3

	lh_parsopercularis_CT
Coeffcient	Estimates	CI (95%)	p-Value
Intercept	3.09	2.96 – 3.23	<0.001
SES1	0.02	-0.00 – 0.03	0.057
Age	-0.00	-0.01 – -0.00	0.001
Sex	0.02	-0.05 – 0.08	0.638
Observations	69
R2 / R2 adjusted	0.185 / 0.147

	rh_middletemporal_CT
Coeffcient	Estimates	CI (95%)	p-Value
Intercept	3.24	3.07 – 3.42	<0.001
SES1	0.01	-0.01 – 0.04	0.222
Age	-0.00	-0.01 – 0.00	0.068
Sex	0.05	-0.04 – 0.13	0.281
Observations	69
R2 / R2 adjusted	0.075 / 0.032

Associations between SES1 and pars opercularis / middle temporal gyrus are not significant in the Q>=3 dataset, controlling for age, sex/gender, and TBV.

SA Results, INR Q>=4

	rh_parsorbitalis_area
Coeffcient	Estimates	CI (95%)	p-Value
Intercept	36.73	-275.95 – 349.42	0.814
INR	-12.69	-23.72 – -1.66	0.025
TBV	0.00	0.00 – 0.00	0.001
Age	1.36	-1.15 – 3.87	0.279
Sex	-21.74	-92.24 – 48.77	0.537
Observations	46
R2 / R2 adjusted	0.494 / 0.445

INR is associated with rh pars orbitalis area in the Q>=4 dataset, controlling for TBV, age, and sex (although neither age nor sex were significant predictors of RH pars orbitalis SA).

Dx is also not a significant predictor, and there is no significant Dx by INR interaction.

SA Results, INR Q>=3

	rh_parsorbitalis_area
Coeffcient	Estimates	CI (95%)	p-Value
Intercept	-57.62	-306.01 – 190.77	0.643
INR	-11.64	-21.62 – -1.67	0.023
TBV	0.00	0.00 – 0.00	<0.001
Age	0.89	-1.39 – 3.17	0.438
Sex	-34.39	-90.34 – 21.56	0.223
Observations	56
R2 / R2 adjusted	0.551 / 0.516

INR is associated with rh pars orbitalis area in the Q>=3 dataset, controlling for TBV, age, and sex (although neither age nor sex were significant predictors of RH pars orbitalis SA).

Dx is also not a significant predictor, and there is no significant Dx by INR interaction.

SA Results, Neighborhood Advantage: Q>=4

	lh_parsorbitalis_area
Coeffcient	Estimates	CI (95%)	p-Value
Intercept	-32.25	-207.46 – 142.95	0.714
SES1	-10.42	-18.88 – -1.95	0.017
TBV	0.00	0.00 – 0.00	<0.001
Age	2.34	0.92 – 3.75	0.002
Observations	58
R2 / R2 adjusted	0.617 / 0.595

	lh_parsopercularis_area
Coeffcient	Estimates	CI (95%)	p-Value
Intercept	-58.25	-594.31 – 477.81	0.828
SES1	-28.09	-53.97 – -2.20	0.034
TBV	0.00	0.00 – 0.00	<0.001
Age	6.35	2.02 – 10.67	0.005
Observations	58
R2 / R2 adjusted	0.547 / 0.522

Neighborhood advantage is associated with left hemisphere pars orbitalis and pars opercularis SA, controlling for TBV and age.

No significant dx by SES1 interaction term, nor dx main effect.

SA Results, Neighbohood Advantage: Q>=3

	lh_parsorbitalis_area
Coeffcient	Estimates	CI (95%)	p-Value
Intercept	-57.59	-225.59 – 110.41	0.496
SES1	-9.84	-18.66 – -1.02	0.029
TBV	0.00	0.00 – 0.00	<0.001
Age	2.36	0.94 – 3.79	0.002
Observations	69
R2 / R2 adjusted	0.593 / 0.574

	lh_parsopercularis_area
Coeffcient	Estimates	CI (95%)	p-Value
Intercept	123.92	-383.01 – 630.85	0.627
SES1	-17.55	-44.16 – 9.06	0.192
TBV	0.00	0.00 – 0.00	<0.001
Age	5.60	1.30 – 9.91	0.012
Observations	69
R2 / R2 adjusted	0.455 / 0.430

	rh_parstriangularis_area
Coeffcient	Estimates	CI (95%)	p-Value
Intercept	-470.22	-1057.97 – 117.54	0.115
SES1	-38.02	-68.88 – -7.17	0.017
TBV	0.00	0.00 – 0.00	<0.001
Age	4.08	-0.91 – 9.08	0.108
Observations	69
R2 / R2 adjusted	0.485 / 0.461

Neighborhood advantage associated with left hemisphere and pars orbitalis SA, as in the Q>=4 dataset,

Neighborhood advantage is not significantly associated with pars opercularis SA in the Q>=3 dataset (in contrast to Q>=4).

Neighborhood advantage is also associated with right hemisphere pars triangularis SA (not significant in the Q>=4 dataset

SA Results: Zip-Income, Q>=4

	lh_parsorbitalis_area
Coeffcient	Estimates	CI (95%)	p-Value
Intercept	32.71	-162.80 – 228.21	0.737
Zip-Income	-0.00	-0.00 – -0.00	0.039
TBV	0.00	0.00 – 0.00	<0.001
Age	1.51	-0.04 – 3.07	0.056
Observations	47
R2 / R2 adjusted	0.570 / 0.540

Zip-Income is negatively associated with lh pars orbitalis SA in the Q>=4 dataset. Visualizing the partial regression plot here also.